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arXiv · 2211.15538

Graph Convolutional Network for Multi-Target Multi-Camera Vehicle Tracking

Elena Luna·Juan Carlos San Miguel·José María Martínez·Marcos Escudero-Viñolo
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Abstract

This letter focuses on the task of Multi-Target Multi-Camera vehicle tracking. We propose to associate single-camera trajectories into multi-camera global trajectories by training a Graph Convolutional Network. Our approach simultaneously processes all cameras providing a global solution, and it is also robust to large cameras unsynchronizations. Furthermore, we design a new loss function to deal with class imbalance. Our proposal outperforms the related work showing better generalization and without requiring ad-hoc manual annotations or thresholds, unlike compared approaches.

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Elena Luna, Juan Carlos San Miguel, José María Martínez, Marcos Escudero-Viñolo. 2022-11-28. Graph Convolutional Network for Multi-Target Multi-Camera Vehicle Tracking. https://arxiv.org/abs/2211.15538

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